Literature DB >> 33225533

A low-cost pipeline for soil microbiome profiling.

Anita Bollmann-Giolai1,2, Michael Giolai3, Darren Heavens2, Iain Macaulay2, Jacob Malone1,4, Matthew D Clark3,4.   

Abstract

Common bottlenecks in environmental and crop microbiome studies are the consumable and personnel costs necessary for genomic DNA extraction and sequencing library construction. This is harder for challenging environmental samples such as soil, which is rich in Polymerase Chain Reaction (PCR) inhibitors. To address this, we have established a low-cost genomic DNA extraction method for soil samples. We also present an Illumina-compatible 16S and ITS rRNA gene amplicon library preparation workflow that uses common laboratory equipment. We evaluated the performance of our genomic DNA extraction method against two leading commercial soil genomic DNA kits (MoBio PowerSoil® and MP Biomedicals™ FastDNA™ SPIN) and a recently published non-commercial extraction method by Zou et al. (PLoS Biology, 15, e2003916, 2017). Our benchmarking experiment used four different soil types (coniferous, broad-leafed, and mixed forest plus a standardized cereal crop compost mix) assessing the quality and quantity of the extracted genomic DNA by analyzing sequence variants of 16S V4 and ITS rRNA amplicons. We found that our genomic DNA extraction method compares well to both commercially available genomic DNA extraction kits in DNA quality and quantity. The MoBio PowerSoil® kit, which relies on silica column-based DNA extraction with extensive washing, delivered the cleanest genomic DNA, for example, best A260:A280 and A260:A230 absorbance ratios. The MP Biomedicals™ FastDNA™ SPIN kit, which uses a large amount of binding material, yielded the most genomic DNA. Our method fits between the two commercial kits, producing both good yields and clean genomic DNA with fragment sizes of approximately 10 kb. Comparative analysis of detected amplicon sequence variants shows that our method correlates well with the two commercial kits. Here, we present a low-cost genomic DNA extraction method for soil samples that can be coupled to an Illumina-compatible simple two-step amplicon library construction workflow for 16S V4 and ITS marker genes. Our method delivers high-quality genomic DNA at a fraction of the cost of commercial kits and enables cost-effective, large-scale amplicon sequencing projects. Notably, our extracted gDNA molecules are long enough to be suitable for downstream techniques such as full gene sequencing or even metagenomics shotgun approaches using long reads (PacBio or Nanopore), 10x Genomics linked reads, and Dovetail genomics.
© 2020 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.

Entities:  

Keywords:  DNA cleanup; amplicon library construction; gDNA extraction; microbiome; soil

Mesh:

Substances:

Year:  2020        PMID: 33225533      PMCID: PMC7755778          DOI: 10.1002/mbo3.1133

Source DB:  PubMed          Journal:  Microbiologyopen        ISSN: 2045-8827            Impact factor:   3.139


  34 in total

1.  A strategy for optimizing quality and quantity of DNA extracted from soil.

Authors:  H Bürgmann; M Pesaro; F Widmer; J Zeyer
Journal:  J Microbiol Methods       Date:  2001-05       Impact factor: 2.363

2.  Effect of the extraction and purification of soil DNA and pooling of PCR amplification products on the description of bacterial and archaeal communities.

Authors:  J S Sáenz; F Roldan; H Junca; Z Arbeli
Journal:  J Appl Microbiol       Date:  2019-04-01       Impact factor: 3.772

3.  Removal of humic substances from soil DNA using aluminium sulfate.

Authors:  Dexian Dong; An Yan; Haiming Liu; Xuehong Zhang; Yuquan Xu
Journal:  J Microbiol Methods       Date:  2005-12-27       Impact factor: 2.363

4.  Comparison of three genomic DNA extraction methods to obtain high DNA quality from maize.

Authors:  Amani Abdel-Latif; Gamal Osman
Journal:  Plant Methods       Date:  2017-01-03       Impact factor: 4.993

5.  The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications.

Authors:  Rolf Henrik Nilsson; Karl-Henrik Larsson; Andy F S Taylor; Johan Bengtsson-Palme; Thomas S Jeppesen; Dmitry Schigel; Peter Kennedy; Kathryn Picard; Frank Oliver Glöckner; Leho Tedersoo; Irja Saar; Urmas Kõljalg; Kessy Abarenkov
Journal:  Nucleic Acids Res       Date:  2019-01-08       Impact factor: 16.971

6.  phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.

Authors:  Paul J McMurdie; Susan Holmes
Journal:  PLoS One       Date:  2013-04-22       Impact factor: 3.240

7.  Bioconductor workflow for microbiome data analysis: from raw reads to community analyses.

Authors:  Ben J Callahan; Kris Sankaran; Julia A Fukuyama; Paul J McMurdie; Susan P Holmes
Journal:  F1000Res       Date:  2016-06-24

8.  Improved Bacterial 16S rRNA Gene (V4 and V4-5) and Fungal Internal Transcribed Spacer Marker Gene Primers for Microbial Community Surveys.

Authors:  William Walters; Embriette R Hyde; Donna Berg-Lyons; Gail Ackermann; Greg Humphrey; Alma Parada; Jack A Gilbert; Janet K Jansson; J Gregory Caporaso; Jed A Fuhrman; Amy Apprill; Rob Knight
Journal:  mSystems       Date:  2015-12-22       Impact factor: 6.496

9.  Sample tracking in microbiome community profiling assays using synthetic 16S rRNA gene spike-in controls.

Authors:  Dieter M Tourlousse; Akiko Ohashi; Yuji Sekiguchi
Journal:  Sci Rep       Date:  2018-06-14       Impact factor: 4.379

10.  Spatially resolved transcriptomics reveals plant host responses to pathogens.

Authors:  Michael Giolai; Walter Verweij; Ashleigh Lister; Darren Heavens; Iain Macaulay; Matthew D Clark
Journal:  Plant Methods       Date:  2019-10-10       Impact factor: 4.993

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  1 in total

1.  Sequencing Depth Has a Stronger Effect than DNA Extraction on Soil Bacterial Richness Discovery.

Authors:  Concepcion Sanchez-Cid; Romie Tignat-Perrier; Laure Franqueville; Laurence Delaurière; Trista Schagat; Timothy M Vogel
Journal:  Biomolecules       Date:  2022-02-25
  1 in total

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